The present invention relates to the field of automated biomarker expression analysis in tissue samples using algorithms to enhance operator-independent analysis and assay result reproducibility for greater predictive value in diagnostic assays.
To date, biomarker assessment on tissue sections relies on traditional cytochemical and immunohistochemical (IHC) techniques which were largely developed before large scale and high throughput assays were available. A significant drawback to traditional methods is the subjective nature of the test, and lack of standardization. Although IHC tests have shown clinical utility (e.g., Her2/HercepTest), the value of these tests have recently been shown to be compromised by the site at which the test is performed. Two recent studies examining the reproducibility of Her2 testing has shown that there may be as much as 20% error between local and central lab testing (Perez et al. J. Clinic. One. (2006) 24:3032-8; Paik S et al. Benefit from adjuvant trastuzumab may not be confined to patients with IHC 3+ and/or FISH positive tumors: Central testing results from NSABP B-31 (2007) 25:511-22).
Tissue microarray technology offers the opportunity for high throughput analysis of tissue samples (Konen, J. et al., Nat. Med. 4:844-7 (1998); Kallioniemi, O. P. et al., Hum. Mol. Genet. 10:657-62 (2001); Rimm, D. L. et al., Cancer J. 7:24-31 (2001)). For example, the ability to rapidly perform large scale studies using tissue microarrays can provide critical information for identifying and validating drug targets and prognostic markers (e.g. estrogen receptor (ER) and HER2/neu), as well as candidate therapeutics.
The present invention provides for the first time fully automated standardization of in situ biomarker quantification that minimizes lab-to-lab, machine-to-machine, operator-to-operator, and day-to-day staining variations.